Dopamine (DA) is a critical neurotransmitter, conserved from C. elegans to man, that regulates a wide variety of behaviors, including learning and memory, courtship behaviors, reward-seeking, and sleep/wake rhythms. Dysfunction of DA neural circuits in turn contributes to disorders such as Parkinson's disease, depression, and drug addiction. Yet how DA neural circuits contribute to these behaviors or disorders is not well-understood. The goal of this work is to develop, characterize, and utilize novel genetic reagents for the dissection of the DA neural network in Drosophila melanogaster. Drosophila is an ideal system to carry out these studies, as fruit flies have only ~250 DA neurons to drive many of the same DA-dependent behaviors found in mammals. Moreover, flies are highly tractable to neural circuit analyses, as they have a short generation time, well- developed genetic techniques and resources, and can be easily maintained in large numbers. In previous work, we generated novel transgenic fly lines that allowed us to manipulate distinct subsets of DA neurons. Using these lines, we identified a single pair of DA neurons that promote arousal by projecting to and directly inhibiting a sleep-promoting circuit. In addition, we have recently developed a novel genetic method, CLAMP (Cell Labeling Across Membrane Partners), which allows for identification, morphological characterization, and functional manipulation of neurons based solely on connectivity patterns. Here, we propose to generate novel transgenic DA driver lines, which will be used for the identification, characterization, and connectivity mapping of the DA neural network in the fly brain. First, we will generate new DA transgenic fly lines, based on the genomic enhancers from different genes that express in DA cells. Second, we will screen established Gal4 lines for expression in subsets of DA cells. By using a combinatorial genetic intersectional approach, these fly lines will collectively generate ~22,600 distinct labeling patterns containing small subsets of DA neurons. These lines will be made available to the scientific community to facilitate functional analyses of the DA neural network. Third, we will create a comprehensive database of DA neurons in the fly brain by 1) identifying and naming individual DA cells and 2) by using computer tracing techniques combined with registration to a standard brain model to label projection patterns. Fourth, by using the CLAMP method to systematically map the connectivity of these DA neurons, we will develop a detailed model of the DA neural network in Drosophila. Understanding how DA circuits in Drosophila function to regulate different behaviors would provide insights into related mechanisms in mammals, including humans, and thus set the stage for circuit-based therapeutic interventions for specific neurological and psychiatric diseases.